Amnon SonnenbergMD MSc

Although, at a first glance, medical decision analysis appears to be focused primarily on techniques of how to optimize choices among alternative medical tests and therapies, a closer look will soon reveal that it deals with a much broader aspect of medicine. In essence, medical decision analysis constitutes a large assortment of mathematical methods to study the entire theoretical underpinning of medical practice. It tries to solve such questions as: How does a medical test actually function? What is the best test to choose among multiple competing test options? What is the most efficacious sequence of medical tests? How do physicians recognize a disease pattern? How do physicians solve medical riddles, and how do they extract a diagnostic hypothesis from a bewildering array of clinical signs and symptoms? When is it time to stop a diagnostic pursuit and start therapy? In a population of human subjects, who benefits most from what type of medical management? What is the best therapy to choose among alternative therapies? How does one arrange the most efficacious and least expensive medical management strategy? In dealing with such questions, medical decision analysis has adopted techniques from operation research, business management, economics, psychology, probability theory, and statistics.

The armamentarium of decision analysis contains a large variety of tools, including decision trees, threshold analyses, Markov chains, Bayes analysis, receiver operation characteristics, waiting line theory, compartment models, linear programming, discrete event simulations, Monte Carlo simulations, Monte Carlo Markov Chain modeling, prospect theory, and many more. In addition to some general textbooks about decision analysis, there are multiple treatises that deal exclusively with individual techniques, such as decision trees, receiver operation characteristics, waiting lines, or linear programming. Most investigators in medical decision analysis use dedicated software to design and execute their mathematical models. It should be obvious from these introductory remarks that a single chapter on medical decision analysis can only present a small piece from a much larger pie.

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